Application of factor neural network in multiexpert system for oil-gas reservoir protection

Li Yang, Lixue Chen, Xinyu Gen, Lin Wang, Jun Zhang

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Knowledge representation and reasoning model play an important role in multi-expert system. In this paper, a new knowledge representation method, factor neural network theory(FNN), is used in multi-expert system for oil-gas reservoir protection. Firstly, by introducing factor and factor space theory, knowledge representation model based on factor state space is presented. Secondly, analog factor neural network structure is analyzed to solve reasoning problem of expert system. For illustration, fuzzy reasoning theory is utilized in factor neural network to verify the effectiveness of our proposed method. The application of the expert system shows that factor neural network theory is valid in knowledge representation and reasoning model and blackboard mechanism based on point-to point can solve the communication problem among sub-expert systems better. As a result, our proposed method based on FNN can effectively improve the accuracy of inference results.

Original languageEnglish
Pages (from-to)303-308
Number of pages6
JournalJournal of Theoretical and Applied Information Technology
Issue number1
StatePublished - Dec 2012


  • Agent
  • Analog Factor Neuron
  • FNN
  • Oil-Gas Reservoir Protection

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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